Neuron Explorer

Qwen3-0.6B

'return' or 'exit' in code talk

A neuron in layer 8 of Qwen3-0.6B. Its strongest snippets are mixed: they peak on different tokens. It is featured, so it has steering outputs.

What this neuron does

This neuron fires on words about returning a result or leaving a function, such as "return" in a coding explanation or "exit" for leaving a loop or recursion. Turning it up led to talk about how to handle outcomes, while turning it down led to a rambling, repetitive answer.

Written by Claude from this neuron's activations and steering outputs. Confidence: medium. Think it is wrong? Flag it (opens a prefilled issue on GitHub).

Fires most on

The text windows where this neuron's activation was highest. Amber marks positive activation; the outlined token is the peak. Hover a token for its strength.

  1. #1 peak

    True, obj)". If it failed, you might return "(False, reason)". Often, you can use exceptions to handle this situation.⏎Sometimes you might want to return objects of different types based on arguments to the function. For instance, did the

  2. #2 peak

    looks like this:⏎following as appropriate:⏎This is a bool to indicate success.⏎If unsuccessful, this is a Pylons response object that your⏎controller can return. It will contain an appropriate error⏎message for the user.⏎Upon success,

  3. #3 peak

    This increases durability and ensures that you can continue using this set again and again.⏎How will you receive the resource?⏎After your payment has processed you will be redirected to a download page where you can immediately download the file and save it to your computer

  4. #4 peak

    having the x if you set total to 0 at the start because total will never increase, and that's even if you ignore that there is no way to exit the recursion.⏎Also, because total is a local variable and you

  5. #5 peak

    don't know what happened to it, but I probably never completed it anyways.⏎And that recursive function looks really....recursive. I don't see any code to exit out of the loop, IE it will continue to call it self over and over

  6. #6 peak

    )".⏎Sometimes you might want to return objects of different types based on whether an operation succeeded or not. For instance, if the operation was successful, you might return "(

Steering

Push this neuron up or down while the model writes, and watch what changes. The outputs were generated ahead of time, so nothing runs in your browser.

turned down a lot
Prompt

Here is something I have been thinking about lately: 1. A. Monday-Friday: Monday-Sunday (Spa Day) 2. Wednesday-Thursday (Spa Day) 3. Friday (Special Day) 4. Special Event 5. Last Week's Event

Most negative on

Where the activation went furthest below zero. Blue marks negative activation. Many neurons mean something different in each direction.

  1. #1 peak

    expression were noted in transplant recipients. These studies suggest a specific strategy for LAD gene therapy that may be effective and safe.<|endoftext|>The resource has been added to your collection⏎This interactive activity adapted from NOVA Online features animations that illustrate the components

  2. #2 peak

    words by clicking on the first and last letters, in any order. If the selected letters match an item in the list, the letters are highlighted and the item is crossed out. Spaces, capitalization and diàçritîcš are

  3. #3 peak

    . It is an extension of Bullseye matrix problem.⏎Who has power to do everything in this world?⏎Close MATLAB with keyboard⏎Find the treasures in MATLAB Central and discover how the community can help you!⏎Choose a web site to get translated

  4. #4 peak

    , to the assets of the company in the event of its dissolution. Dividends are usually set at a fixed annual rate that must be paid before dividends are distributed to the common stockholders. Preferred stock may be participating, meaning that its holders

Connections

Show on map

Which neurons in earlier layers feed this one, and which later ones it feeds. Amber links excite, blue links suppress; longer bars are stronger.

Fed by earlier layers

  1. L5:688 excites
  2. L7:390 suppresses
  3. L7:906 suppresses
  4. L6:2618 excites
  5. L6:652 suppresses
  6. L7:1840 weakly suppresses
  7. L7:2065 weakly suppresses
  8. L7:648 weakly suppresses
  9. L6:693 weakly suppresses
  10. L2:2662 weakly excites
  11. L6:2115 weakly excites
  12. L2:558 weakly suppresses
  13. L4:1413 weakly excites
  14. L6:1515 weakly suppresses
  15. L7:2383 weakly excites
  16. L7:274 weakly excites
  17. L4:824 weakly suppresses
  18. L6:971 weakly excites
  19. L7:641 weakly excites
  20. L6:1488 weakly excites
  21. L4:14 weakly suppresses
  22. L1:2944 weakly excites
  23. L7:1048 weakly excites
  24. L7:1146 weakly excites

Feeds later layers

  1. L17:2151 excites
  2. L12:492 excites
  3. L11:1030 excites
  4. L10:1591 suppresses
  5. L12:340 suppresses
  6. L11:1350 excites
  7. L13:1953 suppresses
  8. L10:1238 excites
  9. L18:1276 excites
  10. L11:679 weakly excites
  11. L11:1343 weakly excites
  12. L10:2726 weakly suppresses
  13. L10:1691 weakly suppresses
  14. L11:1702 weakly suppresses
  15. L11:1029 weakly suppresses
  16. L11:843 weakly excites
  17. L15:1863 weakly excites
  18. L10:2602 weakly excites
  19. L12:369 weakly excites
  20. L11:1432 weakly excites
  21. L11:2216 weakly excites
  22. L21:2978 weakly suppresses
  23. L10:1554 weakly excites
  24. L21:2970 weakly suppresses

Activation histogram

How often this neuron fires at each strength. Almost always it does close to nothing (the tall bars in the middle); the snippets above are the rare moments it fired hard, amber for positive and blue for negative.

1 values between -0.72 and -0.652 values between -0.65 and -0.592 values between -0.59 and -0.521 values between -0.52 and -0.459 values between -0.45 and -0.3929 values between -0.39 and -0.3276 values between -0.32 and -0.26178 values between -0.26 and -0.19332 values between -0.19 and -0.12707 values between -0.12 and -0.061088 values between -0.06 and 0.01804 values between 0.01 and 0.08375 values between 0.08 and 0.14182 values between 0.14 and 0.2174 values between 0.21 and 0.2827 values between 0.28 and 0.3410 values between 0.34 and 0.412 values between 0.41 and 0.481 values between 0.54 and 0.613 values between 0.61 and 0.672 values between 0.74 and 0.812 values between 0.81 and 0.871 values between 1.87 and 1.94offnegativepositiveoften

Logit lens

The words this neuron nudges the model toward (amber) or away from (blue) when it fires. A hint, not a label: many neurons work through later layers instead.

Promotes

  1. 婴
  2. úb
  3. abound
  4. ifier
  5. WithValue
  6. 的地图
  7. subordinate
  8. 绪
  9. ui
  10. 的心情

Suppresses

  1. rés
  2. achel
  3. ��
  4. cip
  5. artment
  6. amines
  7. oxetine
  8. eni
  9. exem
  10. 物理学